A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
A study of smoothing methods for language models applied to information retrieval
ACM Transactions on Information Systems (TOIS)
LDA-based document models for ad-hoc retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
CLEF 2009 ad hoc track overview: TEL and Persian tasks
CLEF'09 Proceedings of the 10th cross-language evaluation forum conference on Multilingual information access evaluation: text retrieval experiments
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This paper presents a report on our participation in the CLEF 2009 monolingual and bilingual ad hoc TEL@CLEF task involving three different languages: English, French and German. Language modeling was adopted as the underlying information retrieval model. While the data collection is extremely sparse, smoothing is particularly important when estimating a language model. The main purpose of the monolingual tasks is to compare different smoothing strategies and investigate the effectiveness of each alternative. This retrieval model was then used alongside a document re-ranking method based on Latent Dirichlet Allocation (LDA) which exploits the implicit structure of the documents with respect to original queries for the monolingual and bilingual tasks. Experimental results demonstrated that three smoothing strategies behave differently across testing languages while the LDA-based document re-ranking method should be considered further in order to bring significant improvement over the baseline language modeling systems in the cross-language setting.